The post-genomic era of biological network alignment
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Published:2015-06-04
Issue:1
Volume:2015
Page:
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ISSN:1687-4153
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Container-title:EURASIP Journal on Bioinformatics and Systems Biology
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language:en
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Short-container-title:J Bioinform Sys Biology
Author:
Faisal Fazle E,Meng Lei,Crawford Joseph,Milenković Tijana
Abstract
Abstract
Biological network alignment aims to find regions of topological and functional (dis)similarities between molecular networks of different species. Then, network alignment can guide the transfer of biological knowledge from well-studied model species to less well-studied species between conserved (aligned) network regions, thus complementing valuable insights that have already been provided by genomic sequence alignment. Here, we review computational challenges behind the network alignment problem, existing approaches for solving the problem, ways of evaluating their alignment quality, and the approaches’ biomedical applications. We discuss recent innovative efforts of improving the existing view of network alignment. We conclude with open research questions in comparative biological network research that could further our understanding of principles of life, evolution, disease, and therapeutics.
Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,Computer Science Applications,General Biochemistry, Genetics and Molecular Biology
Reference118 articles.
1. SF Altschul, W Gish, W Miller, DJ Lipman, Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990). 2. LG Biesecker, JC Mullikin, FM Facio, C Turner, PF Cherukuri, RW Blakesley, GG Bouffard, PS Chines, P Cruz, NF Hansen, JK Teer, B Maskeri, AC Young, NCS Program, TA Manolio, AF Wilson, T Finkel, P Hwang, A Arai, AT Remaley, V Sachdev, R Shamburek, RO Cannon, ED Green, The ClinSeq project: piloting large-scale genome sequencing for research in genomic medicine. Genome Res. 19, 1665–74 (2009). 3. SQ Tsai, AJ Iafrate, JK Joung, Genome editing: a tool for research and therapy: towards a functional understanding of variants for molecular diagnostics using genome editing. Nat. Med. 20, 1103–04 (2014). 4. J Alföldi, K Lindblad-Toh, Comparative genomics as a tool to understand evolution and disease. Genome Res. 23, 1063–68 (2013). 5. H Yu, P Braun, MA Yildirim, I Lemmens, K Venkatesan, J Sahalie, T Hirozane-Kishikawa, F Gebreab, N Li, N Simonis, T Hao, JF Rual, A Dricot, A Vazquez, RR Murray, C Simon, L Tardivo, S Tam, N Svrzikapa, C Fan, AS Smet de, A Motyl, ME Hudson, J Park, X Xin, ME Cusick, T Moore, C Boone, M Snyder, FP Roth, et al., High-quality binary protein interaction map of the yeast interactome networks. Science. 322, 104–110 (2008).
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